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nhigui

Overview

31
Games logged
12 won, 19 lost.
38.7%
Personal win rate
−21.4 pts vs community (60.1%).
1,047
Days active
10.8 games / year on average.
Leo
Favorite investigator
Most-played character.
3
Longest win streak
Consecutive victories in a row.
7
Longest loss streak
Consecutive defeats in a row.

Career arc

Mar 2, 2016
first game
Jan 13, 2019
last game

Wins vs losses

A quick visual tally of this contributor's career so far.

N= 31

Best & worst Ancient One (n ≥ 5)

  • Best Azathoth — 38.5% (n=26)
  • Personal nemesis Azathoth — 38.5% (n=26)
  • Unique AOs faced 5

Net record

−7
12 victories minus 19 defeats. Below the 50/50 line by 11.3 pts.

Ancient Ones

Above or below the curve

For each Ancient One this contributor has faced at least 5 times, the gap between their personal win rate and how the community does against the same foe. Green bars = they beat the community average; red bars = they trail it.

N= 26

Most-faced Ancient Ones

Where this contributor spends their time, split into wins and losses. Bar length is total games against each foe; the green share is how often they won. Sorted by games played.

N= 31

Win rate with confidence range

Same per-AO win rate, but with a 95% confidence band based on sample size. Wide bars = few games (treat with caution). Narrow bars = many games. Only AOs with 2+ games shown.

N= 28

Where they sit among peers

Rank against every other contributor with at least 5 games logged. Higher is better.

N= 718
22%ile

Still learning — outperforms 22% of the cohort.

Repertoire breadth

An effective count of how many Ancient Ones make up this contributor's career — accounts for how lopsided their distribution is. Close to the unique-AO count = broad variety. Close to 1 = one or two favourites dominate.

1.4eff. AOs

Career is concentrated on a few favourites. Top foe: Azathoth (84% of all games). 5 unique AOs ever faced.

All Ancient Ones faced

Click a column header to sort.

N= 31
Ancient One Games Wins Win %
Azathoth 26 10 38.5%
Cthulhu 2 0 0.0%
Nyarlathotep 1 1 100.0%
Shub-Niggurath 1 0 0.0%
Yog-Sothoth 1 1 100.0%

Investigators

Most-played investigators

Where this contributor spends their time on the roster. Sorted by total games with each character.

N= 69

Win rate by investigator

Per-character win rate with a 95% confidence band. Only investigators played 3+ times appear; wide bars mean a small sample.

N= 64

Roster breadth

An effective count of how many investigators make up this contributor's career — it accounts for how lopsided their picks are. Close to the unique count means wide variety; close to 1 means a couple of mains dominate.

9.9eff. chars

Most-played: Leo (16% of all games). 14 unique investigators ever fielded.

Expansions

Expansions mixed per game

How many expansion boxes this contributor typically combines in a single game.

N= 31

Time & Activity

Time at the table

Across 31 timed games. Game length is self-reported; the rare sub-30-minute entries (data slips) are excluded.

N= 31
45h
Roughly 45h 25m spent summoning horrors. Averaging 88 min per game (−83 min vs the community's 171 min).

Game-length distribution

How long this contributor's games run, in minutes. The visible range clips a few long outliers.

N= 31

Quick wins or long grinds?

28min
Their victories average 105 min and defeats 77 min — their wins tend to be the longer grinds.

Win rate by team size

Does this contributor do better solo or in a full party? Win rate against the number of investigators at the table, with a 95% confidence band. Only team sizes with 3+ games shown.

N= 30

Games per year

This contributor's logged games by calendar year — the seasons when they were most active.

N= 31

Win-rate trajectory

A rolling win rate across their career in game order — is their form trending up or down? The dashed line marks the community average.

N= 31

When they log games

Every logged game on a day × hour grid, by the time it was submitted (in the form's own timezone, not this contributor's). Darker cells are busier slots. The strip on top totals games by hour, the strip on the right by weekday. Hover any cell for win rate and average length.

N= 31

Records

Trophy case

Career bests and lifetime tallies.

-7
Best score (lowest win)
35m
Fastest victory
6h
Longest game
5
Biggest team
9
Monsters defeated
5
Investigators lost

How their games end

The split of victory types (green) and defeat causes (red) across this contributor's games.

N= 31

Outcome mix vs community

For each way a game can end, the gap between this contributor's share and the community's. Bars to the right = it happens to them more often than the average player.

N= 31